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  • This dataset details the allometry and leaf trait measurements in three common gardens of fifteen juvenile tree species from the Colombian Andes planted along a thermosequence (14, 22 and 26 deg C) in the Antioquia region of Colombia. Allometric data includes tree diameter at the base, total tree height and height to the first branch, crown diameters, health status, survival and percentage of herbivory attacks over ten measuring campaigns from February 2019 until January 2022. Trait data includes leaf area, thickness, dry weight, leaf mass per area total number of branches and leaves per tree. Regarding the common garden plantations the trees were planted in the ground between November 2019 and January 2019 with planting height ranging between 50 and 100 cm (species dependent). Full details about this dataset can be found at https://doi.org/10.5285/c7ce1610-aba3-4a09-bf7c-1b6c774d597a

  • This dataset provides stream networks for three river basins in eastern Sri Lanka (Mundeni Aru, Maduru Oya and Miyangolla Ela). The stream networks were developed for use in hydrologic modelling and are provided as shapefiles. The work was supported by the Natural Environment Research Council (Grant NE/S005838/1). Full details about this dataset can be found at https://doi.org/10.5285/0537af26-5cab-4381-aca0-d997db421111

  • [This dataset is embargoed]. The following dataset contains information on saplings of woody plant species in invaded subtropical mountain forests (Yungas) over three years. The forests were located in the Horco Molle Experimental Reserve and Parque Sierra de San Javier, Tucumán, Argentina. The data was collected as part of an experiment to investigate the impact of management control on the invasion of non-native species such as Ligustrum lucidum, and other less abundant non-native species, on the dynamics of the woody community. The experiment was conducted between June 2020 and November 2023. This work was carried out as part of NERC grant NE/S011641/1 “Optimising the long-term management of invasive species affecting biodiversity and the rural economy using adaptive management”. Full details about this dataset can be found at https://doi.org/10.5285/4311fa93-fdcc-43bd-bb2e-185118c06ed7

  • This data describes the recovering and isolation processes of Bacteroides spp. strains from human and cattle faecal sources from rural areas in Siaya County (Kenya), and occurred between 7th and 28th of June 2018. The data also includes the detection of bacteriophages (infecting these Bacteroides spp. host strains) in conjunction with traditional faecal indicator organisms in water sources from Kisumu and Siaya County (Kenya) occurring between June 18th 2018 and June 13th 2019. Exact location (coordinates) of the sample points are also described in the data set. A microbiological technique using Bile Esculin Bacteroides (BBE) agar was used for the recovering and isolation processes of Bacteroides spp. strains. Standard ISO (7899-2, 9308-1, 10705-2 and 10705-4) techniques, such as membrane filtration and the double-agar-layer methods, were used for the detection of bacteriophages and traditional faecal indicator organisms. The purpose of data collection was to develop new markers that could identify cattle and/or human sources of faecal contamination, which could be used as part of a Microbial Source Tracking (MST) tool box. Technicians and researchers from the University of Brighton (UK), University of Southampton (UK), from the Victoria Institute for Research on Environment and Development (VIRED) (KE) and from the Kenya Medical Research Institute (KEMRI) (KE) were responsible for the collection and interpretation of data. Full details about this dataset can be found at https://doi.org/10.5285/02c8a6b0-e59e-4278-b9a2-9958cd5a2c3c

  • [This application is embargoed until January 1, 2025]. A collection of python and bash scripts to implement, train and deploy a generative adversarial network for population genetic inferences. The networks have been tuned to be deployed to genomic data from Anopheles mosquitoes. However, the general framework can be applied to other species. It requires the input data to be in Variant Call Format (VCF) format and the simulations need to be in msprime format. Full details about this application can be found at https://doi.org/10.5285/3ae572f6-4862-47ae-b4a0-4b9c496b5b54

  • This dataset details information collected from smallholder oil palm farms in Sabah, Malaysian Borneo. Including: management practices, oil palm fruit yield, understorey vegetation, and soil chemical properties (SOC, total N, total P and available P). We collected data between August to November 2019 from 40 smallholdings (defined as farms < 50 ha) across six governance areas in Sabah. We used responses from face-to-face questionnaires to collect information about their management practices, including Best Management Practices (BMPs), and reported Fresh Fruit Bunch (FFB) yields. We also carried out field surveys on these farms to quantify vegetation cover and soil chemical properties. All smallholder farms had mature fruiting trees i.e. > 8 years since planting. The project received ethical approval from the Biology Ethics Committee, University of York (Ref. SGA201906), and permission from the Sabah Biodiversity Council (Ref. JKM/MBS.1000-2/2 JLD.8), Danum Valley Management Committee (Ref. YS/DVMC/2019/27), and South East Asia Rainforest Research Partnership (project number 18033) for permission to conduct our research in Sabah, Malaysia. This work was funded by the NERC iCASE studentship (NE/R007624/1) and Proforest. Full details about this dataset can be found at https://doi.org/10.5285/38487932-b32a-4b15-9fda-ea812c463466

  • The dataset provides transcripts from focus groups in Salima, Mangochi and Zomba (Malawi). The focus groups' discussions focused on important monthly agricultural activities in association with the climate services and extreme weather events. This outlined how climatic factors affected agricultural decision-making. The data were produced as part of NERC Program Science for Humanitarian Emergencies and Resilience (SHEAR). Grant reference - Improving Preparedness to Agro-Climatic Extremes in Malawi (IPACE-Malawi). Full details about this dataset can be found at https://doi.org/10.5285/199b0046-79a3-4e74-8152-17f10c376671

  • [This nonGeographicDataset is embargoed until April 10, 2025]. This dataset describes measurements of transport of ash by surface runoff using a laboratory setup (flumes). In the experiment, three inflow rates (0.25, 1 and 2 L/min) were applied to two typical ash depths found after wildfires (1 and 3 cm). Variables measured include ash depth (cm), inflow rate (L/min), runoff rate (L/sec), ash transport rate (g/sec), ash concentration in the runoff (g/L). Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/351e2785-5a1e-4dbb-97c1-052f1290f0be

  • This dataset consists of soil dates determined using radiocarbon in profiles from permafrost in subarctic Canada. Depth-specific soil core samples were dated using radiocarbon. Soil cores were sampled during early summer in 2013 and 2014. Each year soil cores were sampled from a peatland plateau, thawing features of the peatland plateau, unburnt and burnt black spruce forests, and additional sites in Yukon and Northwest Territories. Full details about this dataset can be found at https://doi.org/10.5285/fe17ac3b-9a26-48ec-aadd-a3e806f9b5f5

  • [This nonGeographicDataset is embargoed until October 10, 2025]. This dataset contains measurements from smart sensors and cameras monitoring the movement and interaction between two wooden dowels moving downstream in a flume. The following values in the x, y and z direction are provided: position, velocity, linear acceleration, angular velocity and filtered angular velocity. Three uniform flow conditions were tested, and the experiments were repeated about 30 times. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/d176d0af-388b-4a7b-82ca-8fcc38a4ad5d